Amdahl's law in the context of heterogeneous many-core systems – a survey

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IET Computers and Digital Techniques Pub Date : 2020-04-03 DOI:10.1049/iet-cdt.2018.5220

Mohammed A. Noaman Al-hayanni, Fei Xia, Ashur Rafiev, Alexander Romanovsky, Rishad Shafik, Alex Yakovlev

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引用次数: 8

Abstract

For over 50 years, Amdahl's Law has been the hallmark model for reasoning about performance bounds for homogeneous parallel computing resources. As heterogeneous, many-core parallel resources continue to permeate into the modern server and embedded domains, there has been growing interest in promulgating realistic extensions and assumptions in keeping with newer use cases. This study aims to provide a comprehensive review of the purviews and insights provided by the extensive body of work related to Amdahl's law to date, focusing on computation speedup. The authors show that a significant portion of these studies has looked into analysing the scalability of the model considering both workload and system heterogeneity in real-world applications. The focus has been to improve the definition and semantic power of the two key parameters in the original model: the parallel fraction (f) and the computation capability improvement index (n). More recently, researchers have shown normal-form and multi-fraction extensions that can account for wider ranges of heterogeneity, validated on many-core systems running realistic workloads. Speedup models from Amdahl's law onwards have seen a wide range of uses, such as the optimisation of system execution, and these uses are even more important with the advent of the heterogeneous many-core era.

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异质多核心系统背景下的Amdahl定律——综述

50多年来，Amdahl定律一直是同构并行计算资源性能边界推理的标志性模型。随着异构、许多核心并行资源不断渗透到现代服务器和嵌入式领域，人们对发布符合新用例的现实扩展和假设越来越感兴趣。本研究旨在全面回顾迄今为止与Amdahl定律相关的大量工作所提供的观点和见解，重点是计算加速。作者表明，这些研究的很大一部分着眼于分析模型的可扩展性，同时考虑到现实世界应用程序中的工作负载和系统异构性。重点是改进原始模型中两个关键参数的定义和语义能力：并行分数（f）和计算能力改进指数（n）。最近，研究人员展示了可以解释更广泛异质性的正常形式和多部分扩展，并在许多运行现实工作负载的核心系统上进行了验证。Amdahl定律以后的加速模型有着广泛的用途，例如系统执行的优化，随着异构多核心时代的到来，这些用途变得更加重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IET Computers and Digital Techniques 工程技术-计算机：理论方法

CiteScore

3.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： IET Computers & Digital Techniques publishes technical papers describing recent research and development work in all aspects of digital system-on-chip design and test of electronic and embedded systems, including the development of design automation tools (methodologies, algorithms and architectures). Papers based on the problems associated with the scaling down of CMOS technology are particularly welcome. It is aimed at researchers, engineers and educators in the fields of computer and digital systems design and test. The key subject areas of interest are: Design Methods and Tools: CAD/EDA tools, hardware description languages, high-level and architectural synthesis, hardware/software co-design, platform-based design, 3D stacking and circuit design, system on-chip architectures and IP cores, embedded systems, logic synthesis, low-power design and power optimisation. Simulation, Test and Validation: electrical and timing simulation, simulation based verification, hardware/software co-simulation and validation, mixed-domain technology modelling and simulation, post-silicon validation, power analysis and estimation, interconnect modelling and signal integrity analysis, hardware trust and security, design-for-testability, embedded core testing, system-on-chip testing, on-line testing, automatic test generation and delay testing, low-power testing, reliability, fault modelling and fault tolerance. Processor and System Architectures: many-core systems, general-purpose and application specific processors, computational arithmetic for DSP applications, arithmetic and logic units, cache memories, memory management, co-processors and accelerators, systems and networks on chip, embedded cores, platforms, multiprocessors, distributed systems, communication protocols and low-power issues. Configurable Computing: embedded cores, FPGAs, rapid prototyping, adaptive computing, evolvable and statically and dynamically reconfigurable and reprogrammable systems, reconfigurable hardware. Design for variability, power and aging: design methods for variability, power and aging aware design, memories, FPGAs, IP components, 3D stacking, energy harvesting. Case Studies: emerging applications, applications in industrial designs, and design frameworks.